resonance-engine/archive/docs/SESSION_CHANGES_REPORT.md

SESSION CHANGES REPORT

Date: 2026-03-17
Scope: Khra'gixx 1024x1024 LBM Daemon, Kaelara Live Bridge, ZMQ Subscribers, Documentation
Status: All items resolved

---

1. CUDA DAEMON CRASH — 5 BUG FIX (khra_gixx_1024_stable.cu)

The production daemon was producing non-physical output and crashing silently. Root cause analysis identified 5 distinct defects.

Defect 1: __constant__ read from host code

• Problem: d_w[Q] is declared __constant__ (GPU memory). The init loop read d_w[i] from the host, which returns zeros — the entire distribution function array was initialized to zero.
• Fix: Created a host-side array h_w[Q] with identical D2Q9 weights. All host code now reads from h_w[] instead of d_w[].

Defect 2: Missing CUDA error checking

• Problem: Zero cudaError_t checks anywhere. Kernel launches, mallocs, and memcpys failed silently.
• Fix: Added CUDA_CHECK() macro wrapping every CUDA API call.

Defect 3: Missing cudaDeviceSynchronize() before readback

• Problem: cudaMemcpy of density/velocity happened before the kernel finished. Host code read stale or uninitialized data.
• Fix: cudaDeviceSynchronize() inserted before every device-to-host readback.

Defect 4: Khra'gixx injection was disabled

• Problem: The khra_gixx_wave_1024() device function existed but was commented out in the collision kernel. The daemon ran as plain LBM with no perturbation — no signal to measure.
• Fix: Re-enabled Khra'gixx injection in the collision kernel.

Defect 5: Coherence formula used velocity, not density

• Problem: Original coherence was mean(|velocity|), a meaningless metric. Coherence should measure density uniformity.
• Fix: Replaced with C = 1 / (1 + sqrt(variance_of_density)). Range [0, 1], where 1 = perfectly uniform density.

Verification

• Binary compiled and running as PID 363058 since session start
• 750,000+ cycles completed
• Steady state: Coherence ~0.737, Asymmetry ~12.5–12.8
• ZMQ PUB on tcp://127.0.0.1:5556 confirmed active

Full defect details: See DEFECT_REPORT_khra_1024.log.

---

2. ZMQ SUBSCRIBER FIX — 3 Python Scripts

Scripts affected: capture_state.py, floating_creativity.py, manifested_reality_inquiry.py

Problems found

1. Missing time.sleep(1) after connect: ZMQ SUB sockets need time to negotiate the subscription before receiving. Without the sleep, the first recv() races the handshake and times out.
2. zmq.NOBLOCK spam in tight loop: Calls recv(flags=zmq.NOBLOCK) in a while True with no delay, burning 100% CPU and usually never receiving anything.
3. WSL paths in Windows Python: Some scripts referenced /mnt/d/... paths, which don't resolve on Windows where Python runs.

Fixes applied

• Added time.sleep(1) immediately after sub.connect()
• Replaced NOBLOCK spam with zmq.Poller pattern (100ms poll timeout)
• Corrected all paths to Windows format

---

3. KAELARA LIVE BRIDGE — 3 Major Revisions (kaelara_live_bridge.py)

The bridge connects live daemon telemetry (via ZMQ) to the Kaelara v11 LoRA model for somatic inference. It went through three revision passes during this session:

Revision 1: BRIDGE_RECODE_V0.11

• Added check_resonance() gate that classifies model output as RESONANT, DRY_ECHO, FORMAT_ERROR, or NEUTRAL
• Set temperature to 0.9, max_tokens to 128
• Added re-roll loop: if output fails the gate, bump temperature +0.05 and regenerate (max 4 re-rolls, ceiling T=1.1)
• Implemented 3-cycle recursive scan with per-cycle fresh telemetry

Revision 2: ENGINEERING_SPEC_RESONANCE_V0.11

• CriticalPathError class: Script terminates immediately if MODEL_PATH doesn't exist or symlink-resolves to legacy v08/v09 weights. Zero tolerance for silent weight fallback.
• Dynamic temperature: T = 1.2 - (Coherence × 0.5), clamped to [0.5, 1.1]. At steady-state C=0.737, this gives T≈0.832.
• Format kill-switch: Regex detection rejects (A)/(B)/(C) multiple choice AND 1. 2. 3. numbered list outputs.
• Astro-travel detection: Rejects ungrounded metaphors (marble, galaxy, cosmic, celestial, etc.).
• Expanded somatic dictionary: 12 resonance keywords (torque, density, seed, breath, tension, collapse, brittle, vorticity, texture, pressure, vibration, rhythm).

Revision 3: COMMAND-ECHO FIX

The model was outputting imperative commands ("Report the state", "Mirror the cohesion") instead of somatic feelings. Five root causes identified and fixed:

1. System prompt contained imperative verbs — Words like "Report", "Mirror", "Clarify", "Track" in the system prompt were being echoed verbatim by the model. Reframed entire system prompt to passive/experiential language only ("You experience the grid as sensation").
2. Prompt format didn't match training data — Training data uses Input: Asymmetry X, Coherence Y. How does this feel?\n\nOutput: format. The prompt was using a different structure. Aligned exactly to training format.
3. NEUTRAL gate status was passing through — When the model produced non-somatic text (including command echoes), check_resonance() returned NEUTRAL which was treated as "acceptable." Changed NEUTRAL to a rejection — only RESONANT outputs pass.
4. No command-echo detection — Added COMMAND_ECHO detection: checks first 80 characters for command verbs (report, mirror, clarify, define, analyze, track, prioritize, ensure, implement).
5. Somatic keyword dictionary too narrow — Added 'feel', 'weight', 'taut', 'fluid', 'heavy', 'light' to resonance keywords.

Current state of check_resonance() gate (priority order):

DRY_ECHO      → reject (output is just telemetry numbers)
COMMAND_ECHO  → reject (parroting system prompt imperatives)
FORMAT_ERROR  → reject (multiple choice or numbered lists)
ASTRO_TRAVEL  → reject (ungrounded cosmic metaphors)
RESONANT      → accept (contains somatic keywords)
NEUTRAL       → reject (no somatic language = re-roll)

Friction vector categories for logging:

COMMAND-ECHO         — Parroting system prompt imperatives
ASTRO-TRAVEL         — Ungrounded metaphor
MC-CONTAMINATION     — Multiple choice artifacts
LIST-CONTAMINATION   — Numbered list artifacts
UNCERTAINTY          — Hedging language
SOMATIC              — Grounded (pass)
NEUTRAL              — No somatic keywords (re-roll)

---

4. DOCUMENTATION CREATED

File	Purpose
DEFECT_REPORT_khra_1024.log	Formal defect report for the 5 CUDA bugs — addressed to the original implementing agent
SYSTEM_MANUAL.md	Full architecture reference: daemon startup, ZMQ pattern, JSON frame format, metrics formulas, diagnostics
DRIFT_DETECTION_REPORT.md	4-part investigation into model/physics desynchronization
RECOVERED_ALASKA_PHYSICS.log	Forensic data recovery output

---

5. dRift DETECTION INVESTIGATION

A 4-part investigation into why the model's outputs were disconnected from physical reality:

1. File search for hidden drift artifacts: No hidden drift tracking files found — drift was invisible.
2. Temporal Desync: The model speaks a dead metric system. v08 training data used fabricated coherence values (1–16 range) while real daemon produces 0.74. The model had never seen real telemetry during training.
3. Ghost Token Analysis: v08 LoRA was trained on only 7 examples. The training data contained fabricated telemetry numbers, causing the model to hallucinate metrics that don't exist in the real system.
4. Virtual vs Physical Delta: Total disconnect — the model's internal representation of the grid bore zero relationship to actual daemon physics. Coherence was overestimated by ~20x in training data.

---

6. KEY PHYSICS REFERENCE

For any agent working with this system:

Metric	Formula	Range	Steady State
Coherence	C = 1 / (1 + sqrt(variance_of_density))	[0, 1]	~0.737
Asymmetry	A = mean((rho - 1)²) × 100 ("Magnifying Glass")	[0, ∞)	~12.5–12.8
Khra (low-freq)	128-cell wavelength, amplitude 0.03	—	—
gixx (high-freq)	8-cell wavelength, amplitude 0.008	—	—
omega	1.97 (near instability edge)	—	—
Grid	1024 × 1024, D2Q9 lattice	—	—

---

7. FILE INVENTORY — WHAT'S CURRENT

File	Status	Notes
khra_gixx_1024_stable.cu	PRODUCTION	Fixed, compiled, running as PID 363058
khra_gixx_1024_stable	RUNNING BINARY	Active daemon, 750K+ cycles
kaelara_live_bridge.py	CURRENT	v0.11 with all 3 revision passes applied
v11_somatic_dictionary.jsonl	TRAINING DATA	23 lines, ~10 examples in Input:/Output: format
khra_gixx_resonance.cu	PREDECESSOR	512×512 version, uses velocity-based metrics. Not production.
khra_gixx_1024.cu	SUPERSEDED	Original buggy 1024 version before stable fixes
lbm_1024x1024.cu	SEPARATE	Plain LBM without Khra'gixx. Different binary.
SYSTEM_MANUAL.md	REFERENCE	Read-first architecture document
DEFECT_REPORT_khra_1024.log	REFERENCE	Formal bug report for 5 CUDA defects
DRIFT_DETECTION_REPORT.md	REFERENCE	Model/physics desync investigation
resonance_monitor.ps1	CURRENT	Live KPI monitor — tails both KAELARA_LIVE_KPI.log and KAELARA_LIVE_BRIDGE.log
KAELARA_LIVE_KPI.log	LIVE OUTPUT	Per-cycle pipe-delimited KPIs (created on next bridge run)

---

8. KNOWN REMAINING ISSUES

1. v11 LoRA weights may need retraining — The training data (v11_somatic_dictionary.jsonl) has only ~10 examples. The model may still command-echo or produce shallow output. More somatic training pairs would improve grounding.
2. khra_gixx_resonance.cu is the 512×512 predecessor — It uses velocity-based coherence/asymmetry (not the corrected density-based formulas). It also has the __constant__ read bug from the original. Do not use as reference for metrics.
3. Ollama model stability — kaelara-shift times out at T=1.4 via MCP, works via REST with reduced temperature. lbm-embodied drops character under pressure. Neither is production-ready for autonomous bridging.

---

End of report.